7 citations · 11 across the 7 of their papers we have counts for
8 papers
NIR: Approximate Neural Instance Retrieval for ALCIQ
N'Dah Jean Kouagou, Pritilata Saha, Caglar Demir +1
Instance retrieval is the main bottleneck of concept-learning systems based on refinement operators. We present NIR, a family of neural instance retrievers for ALCIQ that output gr…
Benchmarking Knowledge Editing using Logical Rules
Tatiana Moteu Ngoli, NDah Jean Kouagou, Hamada M. Zahera +1
Large Language Models (LLMs) are increasingly deployed in real-world applications that require access to up-to-date knowledge. However, retraining LLMs is computationally expensive…
Resilience in Knowledge Graph Embeddings
Arnab Sharma, N'Dah Jean Kouagou, Axel-Cyrille Ngonga Ngomo
In recent years, knowledge graphs have gained interest and witnessed widespread applications in various domains, such as information retrieval, question-answering, recommendation s…
Inference over Unseen Entities, Relations and Literals on Knowledge Graphs
Caglar Demir, N'Dah Jean Kouagou, Arnab Sharma +1
In recent years, knowledge graph embedding models have been successfully applied in the transductive setting to tackle various challenging tasks including link prediction, and quer…
Improving rule mining via embedding-based link prediction
N'Dah Jean Kouagou, Arif Yilmaz, Michel Dumontier +1
Rule mining on knowledge graphs allows for explainable link prediction. Contrarily, embedding-based methods for link prediction are well known for their generalization capabilities…
Universal Knowledge Graph Embeddings
N'Dah Jean Kouagou, Caglar Demir, Hamada M. Zahera +4
A variety of knowledge graph embedding approaches have been developed. Most of them obtain embeddings by learning the structure of the knowledge graph within a link prediction sett…
Neural Class Expression Synthesis
N'Dah Jean Kouagou, Stefan Heindorf, Caglar Demir +1
Many applications require explainable node classification in knowledge graphs. Towards this end, a popular ``white-box'' approach is class expression learning: Given sets of positi…
Learning Concept Lengths Accelerates Concept Learning in ALC
N'Dah Jean Kouagou, Stefan Heindorf, Caglar Demir +1
Concept learning approaches based on refinement operators explore partially ordered solution spaces to compute concepts, which are used as binary classification models for individu…